A Multi-Objective Trajectory Planning Method for Collaborative Robot

被引:30
作者
Lan, Jiangyu [1 ]
Xie, Yinggang [1 ]
Liu, Guangjun [2 ]
Cao, Manxin [1 ]
机构
[1] Beijing Informat Sci & Technol Univ, Sch Informat & Commun Engn, Beijing 100101, Peoples R China
[2] Ryerson Univ, Dept Aerosp Engn, Toronto, ON M5B 2K3, Canada
基金
北京市自然科学基金;
关键词
collaborative robot; trajectory planning; B-spline; multi-objective optimization; MANIPULATORS; ALGORITHM;
D O I
10.3390/electronics9050859
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Aiming at the characteristics of high efficiency and smoothness in the motion process of collaborative robot, a multi-objective trajectory planning method is proposed. Firstly, the kinematics model of the collaborative robot is established, and the trajectory in the workspace is converted into joint space trajectory using inverse kinematics method. Secondly, seven-order B-spline functions are used to construct joint trajectory sequences to ensure the continuous position, velocity, acceleration and jerk of each joint. Then, the trajectory competitive multi-objective particle swarm optimization (TCMOPSO) algorithm is proposed to search the Pareto optimal solutions set of the robot's time-energy-jerk optimal trajectory. Further, the normalized weight function is proposed to select the appropriate solution. Finally, the algorithm simulation experiment is completed in MATLAB, and the robot control experiment is completed using the Robot Operating System (ROS). The experimental results show that the method can achieve effective multi-objective optimization, the appropriate optimal trajectory can be obtained according to the actual requirements, and the collaborative robot is actually operating well.
引用
收藏
页数:18
相关论文
共 30 条
[21]  
Schuetz C., 2015, P 2015 IEEE INT C RO
[22]  
Shi X., 2016, P 2016 IEEE INT C ME
[23]  
Siciliano B, 2009, ADV TXB CONTR SIG PR, P1
[24]   PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [J].
Tian, Ye ;
Cheng, Ran ;
Zhang, Xingyi ;
Jin, Yaochu .
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 2017, 12 (04) :73-87
[25]   INSGA-II based multi-objective trajectory planning for manipulators [J].
Wang, Hui-Fang ;
Zhu, Shi-Qiang ;
Wu, Wen-Xiang .
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science), 2012, 46 (04) :622-628
[26]   Time-optimal trajectory planning for hyper-redundant manipulators in 3D workspaces [J].
Xidias, Elias K. .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2018, 50 :286-298
[27]   Comparison of pharmacokinetics of phytoecdysones and triterpenoid saponins of monomer, crude and processed Radix Achyranthis Bidentatae by UHPLC-MS/MS [J].
Yang, Liu ;
Jiang, Hai ;
Yan, Meiling ;
Xing, Xudong ;
Guo, Xinyue ;
Man, Wenjing ;
Hou, Ajiao ;
Yang, Bingyou ;
Wang, Qiuhong ;
Kuang, Haixue .
XENOBIOTICA, 2020, 50 (06) :677-684
[28]   Towards an optimal avoidance strategy for collaborative robots [J].
Zanchettin, Andrea Maria ;
Rocco, Paolo ;
Chiappa, Simone ;
Rossi, Roberto .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2019, 59 :47-55
[29]   MOEA/D: A multiobjective evolutionary algorithm based on decomposition [J].
Zhang, Qingfu ;
Li, Hui .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2007, 11 (06) :712-731
[30]   A competitive mechanism based multi-objective particle swarm optimizer with fast convergence [J].
Zhang, Xingyi ;
Zheng, Xiutao ;
Cheng, Ran ;
Qiu, Jianfeng ;
Jin, Yaochu .
INFORMATION SCIENCES, 2018, 427 :63-76